Frequency band selection and processing techniques for media source detection

ABSTRACT

Example methods, apparatus and articles of manufacture (i.e., physical storage media) to perform media source detection based on frequency band selection and processing are disclosed. Example metering methods disclosed herein include comparing frequency band values of a first audio signal with corresponding frequency band values of a second audio signal for a first subset of a set of frequency bands to determine a first comparison result. Disclosed example metering methods also include comparing the frequency band values of the first audio signal with corresponding frequency band values of a third audio signal for a different second subset of the set of frequency bands to determine a second comparison result. Disclosed example metering methods further include determining a source of the first audio signal based on the first comparison result and the second comparison result.

RELATED APPLICATION(S)

This patent arises from a continuation of U.S. patent application Ser.No. 14/332,005 (now U.S. Pat. No. ______), which is entitled “FREQUENCYBAND SELECTION AND PROCESSING TECHNIQUES FOR MEDIA SOURCE DETECTION” andwhich was filed on Jul. 15, 2014. U.S. patent application Ser. No.14/332,005 is hereby incorporated by reference in its entirety.

FIELD OF THE DISCLOSURE

This disclosure relates generally to media source detection and, moreparticularly, to frequency band selection and processing techniques formedia source detection.

BACKGROUND

Some media monitoring systems employ media source detection to determinewhich of several media sources is providing media being presented by amonitored media device. For example, in a typical home environment, atelevision may be communicatively coupled to several different mediasources, such as, but not limited to, a set-top box (STB), a digitalversatile disk (DVD) player, a Blu-ray Disk™ player, a gaming console, acomputer, etc., capable of providing media for presentation by thetelevision. Accurate detection of the active media source providing themedia presented by the monitored media device enables reliableidentification of the media and, thus, accurate crediting of audienceexposure to the media.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an example monitored site including anexample home entertainment system monitored by an example meteremploying frequency band selection and processing techniques for mediasource detection as disclosed herein.

FIG. 2 is a block diagram depicting an example implementation of themeter of FIG. 1.

FIG. 3 is a block diagram of an example trending coefficient determinerthat may be used to implement the example meters of FIGS. 1 and/or 2.

FIG. 4 illustrates an example frequency band determined by the exampletrending coefficient determiner of FIG. 3.

FIG. 5 illustrates an example filter bank including a group of examplefrequency bands determined by the example trending coefficientdeterminer of FIG. 3.

FIG. 6 illustrates an example power spectral density (PSD) determined bythe example trending coefficient determiner of FIG. 3 for the examplefilter bank of FIG. 5.

FIG. 7 illustrates an example variation of the example PSD of FIG. 6 forone frequency band in the example filter bank of FIG. 5, which may berepresented by a trending coefficient determined by the example trendingcoefficient determiner of FIG. 3.

FIG. 8 is a block diagram of an example frequency band selector that maybe used to implement the example meters of FIGS. 1 and/or 2.

FIG. 9 is a block diagram of an example media source comparator that maybe used to implement the example meters of FIGS. 1 and/or 2.

FIG. 10 illustrates and example source matching result output by theexample media source comparator of FIG. 9 using a subset of frequencybands selected by the example frequency band selector of FIG. 8.

FIG. 11 illustrates an example deviation in the time delay associatedwith true positive match results determined by the example meters ofFIGS. 1 and/or 2.

FIG. 12 illustrates an example deviation in the time delay associatedwith false positive match results determined by the example meters ofFIGS. 1 and/or 2.

FIGS. 13A-B collectively form a flowchart representative of examplemachine readable instructions that may be executed to implement theexample meters of FIGS. 1 and/or 2.

FIG. 14 is a flowchart representative of example machine readableinstructions that may be executed to implement the example trendingcoefficient determiner of FIG. 3 and/or a portion of the example machinereadable instructions of FIGS. 13A-B.

FIG. 15 is a flowchart representative of example machine readableinstructions that may be executed to implement the example frequencyband selector of FIG. 8 and/or a portion of the example machine readableinstructions of FIGS. 13A-B.

FIG. 16 is a flowchart representative of example machine readableinstructions that may be executed to implement the example media sourcecomparator of FIG. 9 and/or a portion of the example machine readableinstructions of FIGS. 13A-B.

FIG. 17 is a block diagram of an example processor platform that mayexecute the example machine readable instructions of FIGS. 13A-B, 14, 15and/or 16 to implement the example meters of FIGS. 1 and/or 2, theexample trending coefficient determiner of FIG. 3, the example frequencyband selector of FIG. 8 and/or the example media source comparator ofFIG. 9.

Wherever possible, the same reference numbers will be used throughoutthe drawing(s) and accompanying written description to refer to the sameor like parts, elements, etc.

DETAILED DESCRIPTION

Media source detection techniques employing frequency band selection andprocessing are disclosed herein. Media source detection involvesdetermining which of several possible media sources provided mediapresented by a monitored media device. As noted above, accuratedetection of the active media source providing the media presented bythe monitored media device enables reliable identification of the mediaand accurate crediting of audience exposure to the media. However, atechnical problem in prior media monitoring systems is that the accuracyof media source detection can be reduced due to, for example, ambientnoise degrading the audio signal captured from the monitored mediadevice. Example media source detection techniques employing frequencyband selection and processing as disclosed herein provide technicalsolutions to this technical problem and, thus, are able to mitigate theeffects of ambient noise and improve media source detection accuracyrelative to prior systems.

Example media source detection methods disclosed herein, which are ableto provide such technical solutions, include determining first trendingcoefficients for a first audio signal obtained from a first media sourcein communication with a media device, with the first trendingcoefficients corresponding to a set of frequency bands. Such examplemedia source detection methods disclosed herein also include determiningsecond trending coefficients for a second audio signal obtained frommonitoring media presented by the media device, with the second trendingcoefficients corresponding to the set of frequency bands. For example,the first audio signal may be obtained from an audio line output of thefirst media source, whereas the second audio signal may be obtained froma microphone arranged to sense audio emanating from one or more speakersof or associated with the media device. Such example media sourcedetection methods disclosed herein further include selecting a subset ofthe frequency bands for which the first trending coefficients and thesecond trending coefficients have matching directions, and processingrespective frequency band values of the first audio signal andrespective frequency band values of the second audio signal for thesubset of the frequency bands to determine whether the first mediasource provided the media presented by the media device.

In some disclosed example methods, determining the first trendingcoefficients for the first (e.g., media source) audio signal includesdetermining first frequency band values of the first audio signal forthe set of frequency bands, with the first frequency band valuescorresponding to a first time. Such example methods also includedetermining second frequency band values of the first audio signal forthe set of frequency bands, with the second frequency band valuescorresponding to a second time later than the first time. Such examplemethods further include determining the first trending coefficients tobe ratios of the second frequency band values and the first frequencyband values. In some such example methods, the second trendingcoefficients for the second (e.g., media device) audio signal aredetermined in a similar manner. In some such example methods, a firstone of the first (e.g., media source) trending coefficientscorresponding to a first one of the frequency bands and a first one ofthe second (e.g., media device) trending coefficients corresponding tothe same first one of the frequency bands have matching directions if(1) the first one of the first trending coefficients is greater than oneand the first one of the second trending coefficients is greater thanone, or (2) the first one of the first trending coefficients is lessthan or equal to one and the first one of the second trendingcoefficients is less than or equal to one.

In some disclosed example methods, a first one of the first (e.g., mediasource) trending coefficients corresponding to a first one of thefrequency bands and a first one of the second (e.g., media device)trending coefficients corresponding to the same first one of thefrequency band have matching directions if (1) both the first one of thefirst trending coefficients and the first one of the second trendingcoefficients satisfy a threshold value, or (2) both the first one of thefirst trending coefficients and the first one of the second trendingcoefficients do not satisfy the threshold value.

In some disclosed example methods, the subset of the frequency bands isa first subset of the frequency bands, and selecting the first subset ofthe frequency bands includes selecting a second subset of the frequencybands for which the first trending coefficients and the second trendingcoefficients have matching directions. Such example methods also includedetermining a first number of the second subset of the frequency bandshaving values of the first trending coefficients that most closely matchrespective values of the second trending coefficients for the secondsubset of the frequency bands. Such example methods further includeselecting the first subset of the frequency bands from the first numberof the second subset of the frequency bands.

In some disclosed example methods, processing the respective frequencyband values of the first (e.g., media source) audio signal and therespective frequency band values of the second (e.g., media device)audio signal for the subset of the frequency bands includescross-correlating the respective frequency band values of the firstaudio signal and the respective frequency band values of the secondaudio signal for respective ones of the subset of the frequency bands todetermine correlation results for the respective ones of the subset ofthe frequency bands. Such example methods also include combining thecorrelation results for the respective ones of the subset of thefrequency bands to determine a match result associated with the firstmedia source. Such example methods further include comparing the matchresult to a threshold to determine whether the first media sourceprovided the media presented by the media device. Some such disclosedexample methods additionally include determining a set of match resultsassociated with the first media sources over a time period. Such examplemethods also include determining time delays associated with the matchresults, and comparing a standard deviation of the time delays to asecond threshold to further determine whether the first media sourceprovided the media presented by the media device.

These and other example methods, apparatus, systems and articles ofmanufacture (e.g., physical storage structures) to implement frequencyband selection and processing for medias source detection are disclosedin greater detail below.

FIG. 1 is a block diagram of an example monitored site 100 including anexample home entertainment system 105 monitored by an example meter 110employing frequency band selection and processing techniques for mediasource detection as disclosed herein. The home entertainment system 105of the illustrated example includes an example media device 115 incommunication with several example media sources 120A-D. The examplemedia sources 120A-D include, but are not limited to, an example set-topbox (STB) 120A, an example digital versatile disk (DVD) player 120B, andexample game console 120C, etc. The components of the example homeentertainment system 105 may be connected in any manner, including thatshown in FIG. 1. For example, one or more of the media sources 120A-Dmay be communicatively coupled to the media device 115 via cabledconnections, such as high definition multimedia interface (HDMI) cables,audio cables, etc. In some examples, one or more of the media sources120A-D may be communicatively coupled to the media device 115 via analogand/or digital wireless connections.

In the illustrated example of FIG. 1, the STB 120A can be any set-topbox, such as a cable television converter, a direct broadcast satellite(DBS) decoder, an over-the-air (OTA) digital television (DTV) receiver,etc., which receives a plurality of broadcast channels from a broadcastsource. Typically, the STB 120A selects one of the plurality ofbroadcast channels based on a user input, and outputs one or moresignals received via the selected broadcast channel. In the case of ananalog signal, the STB 120A may tune to a particular channel to obtainprogramming delivered on that channel. For a digital signal, the STB120A may tune to a channel and decode packets of data to obtainprogramming delivered on the selected channel. For example, the STB 120Amay tune to a major channel and then extract a program carried on aminor channel within the major channel. In some examples, the STB 120Aincludes digital video recorder (DVR) functionality to supporttime-shifted presentation of the media provided by the STB 120A. DVRfunctionality implemented by the STB 120A may include, for example,delaying presentation of broadcast media, fast-forwarding and rewindingthe broadcast media, pausing the broadcast media, recording thebroadcast media for later presentation (e.g., while watching other mediabeing broadcast on another channel), etc.

In the illustrated example of FIG. 1, the DVD player 120B can be anytype of DVD player, Blu-ray Disk™ player, optical disk player, etc. Insome examples, the DVD player 120B may provide advanced functionality,such as being able to download streaming media from one or more sourcesaccessible via the Internet.

In the illustrated example of FIG. 1, the game console 120C can be anydevice capable of playing a video game. In some examples, the gameconsole 120C is a dedicated gaming console, such as Microsoft's XboxOne™, Nintendo's Wii™, Sony's PlayStation™, etc. In some examples, thegame console 120C is a portable gaming device, such as Nintendo'sGameBoy™, DS™), etc. In some examples, the game console 120C is apersonal computer, a laptop computer, a tablet computer (e.g., aniPad™), etc.

In the illustrated example of FIG. 1, the media device 115 is depictedas a television, but the media device 115 can be, more generally, anytype of media presenting device. For example, the media device 115 maybe a television and/or display device that supports the NationalTelevision Standards Committee (NTSC) standard, the Phase AlternatingLine (PAL) standard, the Système Électronique pour Couleur avec Mémoire(SECAM) standard, a standard developed by the Advanced TelevisionSystems Committee (ATSC), such as high definition television (HDTV), astandard developed by the Digital Video Broadcasting (DVB) Project, etc.In some examples, the media device 115 may be a multimedia computersystem, a tablet computer (e.g., an iPad™), a smartphone, etc.

The monitored site 100 of the illustrated example also includes theexample meter 110 to monitor the media presented by the media device115. An aspect of media monitoring implemented by the example meter 110of FIG. 1 is media source detection. In the illustrated example, themeter 110 implements media source detection employing frequency bandselection and processing, as disclosed herein, to identify which one ofthe example media sources 120A-D is actively providing the media beingpresented by the media device 115. To perform media source detection,the example meter 110 monitors audio signals output by the media device115 and the media sources 120A-D. As such, the example meter 110includes an example media device input 125 to receive an audio signalcorresponding to the media device 115, and example source inputs 130A-Dto receive audio signals corresponding to respective ones of the mediasources 120A-D. In some examples, the media device input 125 is alsoreferred to as a reference input 125 because the audio signal obtainedfrom the media device 115 can be considered a reference audio signal tobe compared against the audio signals from the media sources 120A-D.

In some examples, such as the example illustrated in FIG. 1, the meter110 employs an example microphone 135 and/or other audio/acoustic sensorto non-invasively capture audio emanating from the speaker(s) of themedia device 115 (or from separate speaker(s), such as those of a hometheater system, being driven by the media device). In the illustratedexample, the microphone 135 captures an audio signal from the mediadevice 115 and provides it to the reference input 125 of the meter 110.In the illustrated example of FIG. 1, the source inputs 130A-D of themeter 110 receive audio signals from the media sources 120A-D via wired(e.g., cabled) connections. For example, the source inputs 130A-D may beaudio line inputs communicatively coupled to respective ones of themedia sources 120A-D via example splitters 140A-D, as shown. Because theaudio signals obtained via the reference input 125 and the source inputs130A-D may take different audio paths (e.g., via the microphone 135 vs.via direct cabled connections), there may be delays between thereference audio signal obtained for the media device 115 and the sourceaudio signals obtained for the media sources 120A-D. Accordingly, whencomparing the media device audio signal obtained via the reference input125 with the source audio signals obtained via the source inputs 130A-D,the meter 110 of the illustrated example accounts for signal shifts overan allowed delay range, such from −1 second to +5 seconds, or any otherappropriate range.

In the illustrated example of FIG. 1, the meter 110 determines meteringdata that includes, among other things, media source detection resultsidentifying which media source 120A-D provided the media presented bythe media device 115 at successive monitoring times (also referred toherein as media source detection times). The monitoring times (mediasource detection times) may occur at regular intervals (e.g., such asintervals of 5 sec., 15 sec., 30 sec., 1 min., 2 min., etc.), inresponse to one or more events, etc. The meter 110 of the illustratedexample stores and reports its metering data via an example network 150to an example data processing facility 155. The data processing facility155 performs any appropriate post-processing of the metering data to,for example, determine audience ratings information, identify targetedadvertising to be provided to the monitored site 100, etc. In theillustrated example, the network 150 can correspond to any type(s)and/or number of wired and/or wireless data networks, or any combinationthereof.

As shown in the illustrated example of FIG. 1, the reference (e.g.,media device) audio signal processed by the meter 110 is obtained viathe microphone 135, whereas the media source signals to be compared tothis reference audio signal are obtained via the line inputs 130A-D.However, in many operating environments, the reference (e.g., mediadevice) audio signal captured via the microphone 135 may be affected(e.g., degraded) by ambient noise 145, such as background noise,conversations between audience members in the vicinity of the mediadevice 115, dogs barking, machinery, etc. To mitigate the effects of theambient noise 145, the meter 110 employs frequency band selection andprocessing techniques for media source detection, as disclosed infurther detail below, which can improve media source detection accuracyrelative to prior media monitoring systems.

Although the example meter 110 of FIG. 1 is depicted as having onereference input 125 and four source inputs 130A-D, the meter 110 is notlimited thereto. For example, the meter 110 of the illustrated examplecan be configured to have any number of reference inputs 125 and/or anynumber of source inputs 130A-D. Also, the example meter 110 of FIG. 1 isnot limited to the reference input 125 being received from themicrophone 135 or the source inputs 130A-D being line inputs (or thesource audio signals being received via cabled connections). Forexample, the meter 110 of the illustrated example can be configured toreceive the reference (e.g., media device) audio signal at the referenceinput 125 via a cabled connection and/or receive the source audiosignal(s) at one or more of the source inputs 130A-D via microphone(s),audio/acoustic sensor(s), frequency probes, etc. More generally, thefrequency band selection and processing techniques for media sourcedetection disclosed herein can be used in almost any scenario in which agood (e.g., original) audio signal is being compared to another audiosignal that may have acquired additional, unwanted audio energy.

A block diagram depicting an example implementation of the meter 110 ofFIG. 1 is illustrated in FIG. 2. In the illustrated example of FIG. 2,the processing performed by the example meter 110 is divided intoseveral stages, which begin with sampling the audio obtained via thesource inputs 130A-D and the reference (e.g., media device) input 125,and end with a media source detection result. In some examples, themedia source detection results include a pairwise media device/mediasource match result expressed as a correlation value (e.g., such as apercentage) and a delay (e.g., in milliseconds) between the matchingmedia device and media source audio signals.

Turning to FIG. 2, the example meter 110 illustrated therein includesexample audio samplers 205A-D to sample the source audio signalsobtained at the source inputs 130A-D of the meter 110. The example meter110 of FIG. 2 also includes an example audio sampler 210 to sample thereference (e.g., media device) audio signal obtained at the referenceinput 125 of the meter 110. In the illustrated example, each of theaudio samplers 205A-D and 210 sample their respective input audiosignals at a sampling rate of 16 kHz with 16 bit resolution, but othersampling rates and/or data resolutions can alternatively be used. Insome examples, the audio samplers 205A-D and 210 are implemented asseparate samplers operating in parallel, whereas in other examples, oneor more (or all) of the audio samplers 205A-D and 210 may be implementedby a single sampler cycling through sampling of the different audiosignals.

In the illustrated example of FIG. 2, the meter 110 includes examplefrequency transformers 215A-D to transform the sampled source audiosignals obtained from the audio samplers 205A-D into frequency domainrepresentations of the respective source audio signals. The examplemeter 110 of FIG. 2 also includes an example frequency transformer 220to transform the sampled reference (e.g., media device) audio signalobtained from the audio sampler 210 into a frequency representation (orfrequency transform) of the reference (e.g., media device) audio signal.In the illustrated example, the frequency transformers 215A-D and 220each implement a 512-point Fast Fourier Transform (FFT) to yieldrespective frequency transforms of their respective audio signals having256 frequency bins having bin widths (or spacing) of 31.25 Hz. However,in other examples, the frequency transformers 215A-D and 220 mayimplement other size FFTs and/or other type(s) of transforms to yieldfrequency representations having different numbers of bins, differentbin width/spacing, etc.

As noted above, in some examples, the audio samplers 205A-D and 210sample their respective input audio signals in parallel. In some suchexamples, the sampling frequencies of the respective audio samplers205A-D and 210 may not be synchronized. In such examples, one or moretechniques may be used by the audio samplers 205A-D and 210 to maintainalignment between the sampled audio signals, and thereby avoidintroducing an artificial delay between the signals. For example, theaudio samplers 205A-D and 210 may implement alignment by tracking theposition of the most recent audio samples in the respective audiobuffers maintained by the audio samplers 205A-D and 210. Then, whenretrieving audio segments for processing by the frequency transformers215A-D and 220, the audio segments are taken starting backwards from thetracked positions of the most recent audio samples in the respectiveaudio buffers. This ensures that the successive processing stages of theexample meter 110 are processing the latest available audio from thereference (e.g., media device) input 125 and each of the source inputs130A-D.

The example meter 110 of FIG. 2 further includes an example trendingcoefficient determiner 225 to determine trending coefficients for eachof the source audio signals obtained via the source inputs 130A-D andfor the reference (e.g., media device) audio signal obtained via thereference input 125. In the illustrated example, for a given input audiosignal, the trending coefficient determiner 225 determines a set oftrending coefficients corresponding respectively to a set of frequencybands by processing the frequency transform of the given input audiosignal (e.g., as determined by the frequency transformers 215A-D and220). For example, the trending coefficient determiner 225 of theillustrated example determines a first set of trending coefficients fora first audio signal obtained via the source input 130A for a firstmedia source, wherein the first set of trending coefficients correspondrespectively to a set of frequency bands. The example trendingcoefficient determiner 225 also determines a second set of trendingcoefficients for the reference (e.g., media device) audio signalobtained via the reference input 125, wherein the second set of trendingcoefficients correspond respectively to the same set of frequency bandsfor which the first set of trending coefficients (for the first mediasource) are determined. The trending coefficient determiner 225 furtherdetermines respective sets of trending coefficients for the media sourceaudio signals obtained via the other source inputs 130B-D, with therespective sets of trending coefficients also corresponding to the sameset of frequency bands. As disclosed in further detail below, thetrending coefficients determined by the trending coefficient determiner225 are used to select (e.g., dynamically) frequency bands of thereference (e.g., media device) audio signal and source audio signals forfurther processing.

A block diagram depicting an example implementation of the trendingcoefficient determiner 225 of FIG. 2 is illustrated in FIG. 3. Turningto FIG. 3, the example trending coefficient determiner 225 illustratedtherein includes an example filter bank aggregator 305 to aggregate theFFT bins of the frequency transforms determined by the frequencytransformers 205A-D and 210 into frequency bands, also referred to asfrequency banks. (In some examples, a filter bank refers to a collectionof FFT bins spanning a given frequency band. For convenience, the termsfilter bank and frequency band are used interchangeably herein.) In theillustrated example, the filter bank aggregator 305 aggregates the 256FFT bins of the frequency transforms determined by the frequencytransformers 205A-D and 210 into 32 frequency bands (or frequency banks)ranging from a low frequency (F_(low)) of 400 Hz to a high frequency(F_(high)) of 8000 Hz (or 8 kHz). The high frequency of 8000 Hz isdetermined by the Nyquist sampling rule (e.g., assuming an audiosampling rate of 16 kHz) and the low frequency of 400 Hz is based on thefrequency characteristics of the media device 115 being monitored.However, in other examples, the filter bank aggregator 305 can aggregatethe same or a different number of input FFT bins into the same or adifferent number of frequency bands (filter banks), and over the same ordifferent frequency range.

In the illustrated example of FIG. 3, the filter bank aggregator 305follows a constant filter quality rule, also referred to as a constant Qrule, for determining the different frequency bands. For example, thefilter bank aggregator 305 of FIG. 3 can use Equation 1 to determine theboundaries between different filter bands (banks):

$\begin{matrix}{{{{frequency}\mspace{14mu} {bank}\mspace{14mu} {boundary}_{i}} = {F_{low} \cdot ( \frac{F_{high}}{F_{low}} )^{\frac{i}{banks}}}},} & {{Equation}\mspace{14mu} 1}\end{matrix}$

In Equation 1, F_(low) is the lowest frequency of the filter bank (e.g.,400 Hz), F_(high) is the highest frequency of the filter bank (e.g.,8000 Hz), banks is the number of frequency bands (filter banks) (e.g.,32), and i ranges from 0 to the value of banks.

The example filter bank aggregator 305 of FIG. 3 uses Equation 1 todetermine frequency bands (filter banks) having a flat frequencyresponse and delimited by two frequency boundaries, a lower boundary andan upper boundary. For example, the filter bank aggregator 305determines the lower boundary (F_(l,i)) and an upper boundary (F_(h,i))for the i^(th) frequency band (filter bank) using the following set ofequations represented by Equation 2:

$\begin{matrix}{{{F_{l,i} = {F_{low} \cdot ( \frac{F_{high}}{F_{low}} )^{\frac{i}{banks}}}},{and}}{F_{h,i} = {F_{low} \cdot {( \frac{F_{high}}{F_{low}} )^{\frac{i + 1}{banks}}.}}}} & {{Equation}\mspace{14mu} 2}\end{matrix}$

In Equation 2, i ranges from 0 to (banks−1), to yield a number of filterbands (filter banks) equal to the value of banks.

In some examples, when aggregating the FFT bins of the frequencytransform of a given audio signal into the frequency bands (filterbanks) having boundaries determined according to Equation 2, the filterbank aggregator 305 overlaps the cut-off point between adjacentfrequency bands (filter banks) by one FFT bin. This can provide asmoother transition between adjacent frequency bands (filter banks), andcan reduce the sensitivity to FFT resolution errors. For example, aslight offset in sampling frequency might result in the energy of afrequency component in one FFT frequency band (filter bank) spillingover into an adjacent FFT bin. By overlapping the cut-off point betweenadjacent frequency bands (filter banks) by one FFT bin, this spilloverenergy can still be included (at least partially) in the proper band(bank).

In some examples, the overlapping of adjacent frequency bands (filterbanks) for frequency band i (or filter bank i) is constructed byapplying a gain factor (e.g., a gain of 0.5 or some other value ≦1) tothe next lower FFT bin before the lower boundary (F_(l,i)) of the i^(th)band (bank), and applying a gain factor (e.g., a gain of 0.5 or someother value ≦1) to the next higher FFT bin after the higher boundary(F_(h,i)) of the i^(th) band (bank). The resulting frequency responsefor the i^(th) frequency band (filter bank) is illustrated by theexample filter bank frequency response 400 depicted in FIG. 4. Anexample of an overall set of frequency bands (filter banks) determinedby the example filter bank aggregator 305 using Equation 1 and Equation2, and with the overlapping illustrated in the example of FIG. 4, isillustrated by the example filter bank response 500 depicted in FIG. 5.The example filter bank response 500 depicted in FIG. 5 includes 32frequency bands (filter banks) starting at 400 HZ and ending at 8000 Hz,and exhibits a logarithmic increase in the width of the frequency bands(filter banks) with increasing frequency.

Returning to FIG. 3, the illustrated example trending coefficientdeterminer 225 also includes an example PSD determiner 310 to determine,for the reference (media device) audio signal and source audio signals,respective frequency band values for the different frequency bands(filter banks) determined by the filter bank aggregator 305. Forexample, the PSD determiner 310 of the illustrated example determines afirst set of frequency band values, which correspond to the set offrequency bands (filter banks) determined by the filter bank aggregator305, for an audio signal obtained via the source input 130A for a firstmedia source. The example PSD determiner 310 also determines a secondset of frequency band values, which correspond to the same set offrequency bands (filter banks) determined by the filter bank aggregator305, for the reference (e.g., media device) audio signal obtained viathe reference input 125. The example PSD determiner 310 furtherdetermines respective sets of frequency band values, which correspond tothe same set of frequency bands (filter banks) determined by the filterbank aggregator 305, for the media source audio signals obtained via theother source inputs 130B-D.

In the illustrated example of FIG. 3, the frequency band valuesdetermined by the PSD determiner 310 are power spectral density (PSD)values. However, other types of frequency band values may be determinedby the PSD determiner 310 in other examples. For example, the PSDdeterminer 310 can determine the frequency band values for a given audiosignal and frequency band (filter bank) to be a PSD value by summing themagnitude values (or squared magnitude values) of the FFT bins for thegiven audio signal that are included in the given frequency band (filterbank) (e.g., after multiplying by an appropriate filter gain, such as again of 0.5 for an overlapping FFT bin or a gain of 1 for anon-overlapping FFT bin). Stated mathematically, the PSD determiner 310of the illustrated example determines the frequency band value for thei^(th) frequency band (filter bank) of a given audio signal by summingthe FFT bin values of the given audio signal according to Equation 3,which is:

PSD_(i)=Σ_(j=1) ²⁵⁶FFT_(j) ·G _(i,j).  Equation 3

In Equation 3, PSD_(i) is the frequency band value (e.g., PSD) for thei^(th) frequency band (filter bank) of the given audio signal, FFT_(j)is the value (e.g., magnitude, squared magnitude, etc.) of the j^(th)FFT bin for the given audio signal, and G_(i,j) is the filter bank gaincoefficient to be applied to the value of the j^(th) FFT bin toaggregate this bin into the i^(th) frequency band (filter bank). Forexample, the filter bank gain coefficient G_(i,j) can have a value ofone (1) for FFT bins in the i^(th) frequency band (filter bank), a valueof zero (0) for FFT bins not in the i^(th) frequency band (filter bank),and a value of 0.5 for FFT bins overlapping with the i^(th) frequencyband (filter bank).

The frequency band values (e.g., PSD values) determined by the PSDdeterminer 310 for a given audio signal and set of frequency bands(filter banks) for an audio spectrogram represent the variation of theaudio signal in the different frequency bands over time. An exampleaudio spectrogram 600 determined by the example PSD determiner 310 ofFIG. 3 for an example input audio signal (e.g., corresponding to thereference (media device) audio signal or a media source audio signal) isillustrated in FIG. 6. The example audio spectrogram 600 depicts thefrequency band values (e.g., PSD) values determined by the PSDdeterminer 310 for a given audio signal over a set of 32 frequency bands(filter banks) and for a duration of approximately 5 seconds.

In the illustrated example of FIG. 6, the 9^(th) frequency band (filterbank) is emphasized to show how the frequency band values (e.g., PSDvalues) of the band vary over time. The frequency band values (e.g., PSDvalues) of the different frequency bands (filter banks) of an audiosignal vary depending on the characteristics of the audio. Additionally,in the case of an audio signal obtained by a microphone or otheraudio/acoustic sensor (e.g., such as the microphone 135), one or more ofthe different frequency bands (filter banks) may be affected by ambientnoise (e.g., such as the ambient noise 145). When comparing thereference (e.g., media device) signal obtained via the microphone 135 tothe audio signal obtained via the line inputs 130A-D from the matchingmedia source 120A-D, the reference audio frequency bands (filter banks)not affected by ambient noise will have similar variations, or trends,as the same frequency bands (filter banks) of the source audio signal.However, the reference audio frequency bands (filter banks) affected byambient noise will generally not have similar variations, or trends, asthe same frequency bands (filter banks) of the source audio signal.Thus, the trending example coefficient determiner 225 processes thefrequency band values (e.g., PSD values) of the reference (media device)audio signal and the source audio signals for a set of frequency bands(filter banks) to determining trending coefficients that characterizethe variations, or trends, of the reference (media device) audio signaland the source audio signals in each of the frequency bands (filterbanks). When comparing the reference (media device) audio signal to anaudio signal from one of the media sources 120A-D, frequency bands(filter banks) having similar trending coefficients for the reference(media device) audio signal and the source audio signal are consideredless likely to be corrupted by ambient noise, whereas frequency bands(filter banks) having different trending coefficients for the reference(media device) audio signal and the source audio signal are consideredmore likely to be corrupted by ambient noise.

Returning to FIG. 3, to determine the trending coefficients, thetrending coefficient determiner 225 of the illustrated example furtherincludes an example PSD ratio evaluator 315. The example PSD ratioevaluator 315 evaluates a ratio of successive frequency band values(e.g., PSD values) for a given audio signal (e.g., reference or source)in a given frequency band to determine a trending coefficient indicatingwhether the frequency band values (e.g., PSD values) for that audiosignal in that band (bank) are increasing or decreasing, and by howmuch. Stated mathematically, for a given audio signal, the trendingcoefficient, k_(i,m) for the i^(th) frequency band (filter bank) at agiven instant of time m can be determined by the example PSD ratioevaluator 315 using Equation 4, which is:

$\begin{matrix}{k_{i,m} = {\frac{{PSD}_{i,m}}{{PSD}_{i,{m - \Delta}}}.}} & {{Equation}\mspace{14mu} 4}\end{matrix}$

In Equation 4, PSD_(i,m) is the frequency band value (e.g., PSD) for thei^(th) frequency band (filter bank) of the given audio signal at time m,and PSD_(i,m-Δ) is the frequency band value (e.g., PSD) for the i^(th)frequency band (filter bank) of the given audio signal at time m−Δ. Inthe illustrated example, Δ corresponds to 32 milliseconds, which is thetime interval between adjacent blocks of audio containing 512 samplessampled at a rate of 16 kHz. Thus, in the example of FIG. 3, thetrending coefficient determiner 225 determines a new trendingcoefficients, k_(i,m) for the frequency band (filter banks) of the givenaudio signal each time a new audio block is obtained, and the trendingcoefficients, k_(i,m) represents how much the given band (bank) isvarying between adjacent audio blocks. However, in other examples, thetime difference, A, used in Equation 4 can be a different timedifference, such as a time difference corresponding to multiple audioblocks, which results in the trending coefficients, k_(i,m) representshow much the given band (bank) is varying between audio blocks spacedfarther apart.

In some examples, the PSD determiner 310 determines the frequency bandvalues of the set of frequency bands (filter banks) for a given audiosignal as running averages (also referred to as a rolling average) ofPSD values. For example, the PSD determiner 310 can include a window ofPSD values in the running average, and update the running of PSD valueseach time a new audio block is obtained and transformed. In someexamples, the PSD determiner 310 uses a window of 1024 ms forcalculating the running average, which corresponds to 32 audio blockswhen the audio blocks contain 512 audio samples sampled at a rate of 16kHz. In other examples, other window sizes and update rates for therunning average can be used. An example sequence of frequency bandvalues 700 for a given frequency band (filter bank) determined by thePSD determiner 310 using a running average of PSD values is illustratedin FIG. 7. In examples in which the PSD determiner 310 determinesfrequency band values as running averages of PSD values, the frequencyband values PSD_(i,m) and PSD_(i,m-Δ) in Equation 4 correspond to therunning average outputs at time m and m−Δ, respectively.

Returning to FIG. 2, the example meter 110 illustrated therein includesan example frequency band selector 230, which uses the trendingcoefficients determined by the example trending coefficient determiner225 to select a subset of frequency bands (filter banks) to be used toperform pairwise comparisons between the reference (e.g., media device)audio signal and respective ones of the audio signals obtained from themedia sources 120A-D. In the illustrated example, for a given reference(e.g., media device) audio signal and source audio signal pair, thefrequency band selector 230 updates the selected subset of frequencybands (filter banks) to be used to perform the pairwise comparison whennew trending coefficients are determined for the reference (e.g., mediadevice) audio signal and/or the source audio signal. For example, thetrending coefficients may be updated by the trending coefficientdeterminer 225 each time a new audio block is captured for the reference(e.g., media device) audio signal and/or the source audio signal (e.g.,at a 32 ms rate in the examples described above) and, thus, the subsetof frequency bands (filter banks) selected by the frequency bandselector 230 for pairwise comparison may be updated at the same rate(e.g., 32 ms in the examples above). Furthermore, in some examples,different subsets of the frequency bands (filter banks) may be selectedfor different reference (e.g., media device) audio signal and sourceaudio signal pairs. For example, at a given instance in time, thefrequency band selector 230 may use the trending coefficients determinedfor the reference (e.g., media device) audio signal and a first sourceaudio signal to select a first subset of the frequency bands (filterbanks) for pairwise comparison of the reference (e.g., media device)audio signal and the first source audio signal, whereas the frequencyband selector 230 may use the trending coefficients determined for thereference (e.g., media device) audio signal and a second source audiosignal to select a different second subset of the frequency bands(filter banks) for pairwise comparison of the reference (e.g., mediadevice) audio signal and the second source audio signal.

A block diagram illustrated an example implementation of the frequencyband selector 230 of FIG. 2 is illustrated in FIG. 8. Turning to FIG. 8,the example frequency band selector 230 illustrated therein includes anexample trending coefficient direction comparator 805 to identifyfrequency bands (filter banks) for which the reference (e.g., mediadevice) audio signal and a given one of the source audio signals havetrending coefficients with matching directions. In some examples, atrending coefficient (k_(i,m)) of the reference (e.g., media device)audio signal for a given frequency band (filter bank) and acorresponding trending coefficient (k_(i,m)) of the given source audiosignal for the same frequency band (filter bank) are determined to havethe same direction if both trending coefficients satisfy a thresholdvalue (e.g., both exceed a value of 1) or both trending coefficients donot satisfy the threshold value (e.g., both do not exceed a value of 1).Conversely, in such examples, the trending coefficient (k_(i,m)) of thereference (e.g., media device) audio signal and the correspondingtrending coefficient (k_(i,m)) of the given source audio signal for thesame frequency band (filter bank) are determined to have differentdirections if one of the trending coefficients satisfies the thresholdvalue (e.g., exceed a value of 1), whereas the other one of the trendingcoefficients does not satisfy the threshold value (e.g., does not exceeda value of 1).

Stated mathematically, to identify a subset of frequency bands (filterbanks) to be used to compare the reference (e.g., media device) audiosignal and a given one of the source audio signals, the trendingcoefficient direction comparator 805 identifies those frequency bands(filter banks) satisfying Equation 5, which is:

$\begin{matrix}{{bank}\mspace{14mu} {is}\mspace{14mu} {selected}\mspace{14mu} {if}\text{:}\mspace{14mu} \{ {\begin{matrix}{{k_{i,m} > T},} & {{for}\mspace{14mu} {both}\mspace{14mu} {the}\mspace{14mu} {reference}\mspace{14mu} {and}\mspace{14mu} {source}\mspace{14mu} {ratio}} \\{{k_{i,m} \leq T},} & {{for}\mspace{14mu} {both}\mspace{14mu} {the}\mspace{14mu} {reference}\mspace{14mu} {and}\mspace{14mu} {source}\mspace{14mu} {ratio}}\end{matrix}.} } & {{Equation}\mspace{14mu} 5}\end{matrix}$

In some examples, the threshold Tin Equation 5 is a value of one (1),which cause the trending coefficient direction comparator 805 to selectfrequency bands (filter banks) for which the trending coefficients ofthe reference and source audio are either increasing (which correspondsto a value greater than 1) or decreasing (which corresponds to a valueless than 1).

In some examples, the subset of frequency bands (filter banks)identified by the trending coefficient direction comparator 805 ashaving trending coefficients with matching directions for the reference(e.g., media device) audio signal and a given source audio signal areselected for use in a pairwise comparison of the reference (e.g., mediadevice) audio signal and the given source audio signal to determinewhether the signals match. In some examples, the example frequency bandselector 230 of FIG. 8 also includes an example trending coefficientvalue comparator 810 to evaluate the subset (e.g., a first subset) offrequency bands (filter banks) identified by the trending coefficientdirection comparator 805 as having trending coefficients with matchingdirections for the reference (e.g., media device) audio signal and thegiven source audio signal to further identify a second subset offrequency bands (filter banks) within the first subset that have theclosest matching values. For example, if the first subset of frequencybands (filter banks) identified by the trending coefficient directioncomparator 805 as having trending coefficients with matching directionsfor the reference (e.g., media device) audio signal and the given sourceaudio signal exceeds a first number (e.g., such as 8 or some othernumber), then the trending coefficient value comparator 810 selects thefirst number (e.g., 8 or some other number) of frequency bands (filterbanks) within the first subset having the closest matching values (e.g.,in terms of absolute difference, ratio, etc.). In such examples, thesecond subset of frequency bands (filter banks) identified by thetrending coefficient value comparator 810 as having trendingcoefficients with closest matching values for the reference (e.g., mediadevice) audio signal and the given source audio signal are selected foruse in the pairwise comparison of the reference (e.g., media device)audio signal and the given source audio signal to determine whether thesignals match.

Returning to FIG. 2, the example meter 110 illustrated therein includesan example media source comparator 235, which uses the subset offrequency bands (filter banks) selected by the frequency band selector230 for a given reference (e.g., media device) audio signal and sourceaudio signal pair to perform a pairwise comparison of the reference andthe given source signal to determine whether the source signal matchesthe reference (e.g., media device) signal. In the illustrated example,the media source comparator 235 uses the different subset of frequencybands (filter banks) selected for each of the different possiblereference and source audio signal pairs to compare each source signalagainst the reference (e.g., media device) signal to identify which oneof the media sources 120A-D is most likely the source of the mediapresented by the media device 115. More specifically, in the illustratedexample, the media source comparator 235 processes the frequency bandvalues of the reference (e.g., media device) audio signal and respectivefrequency band values of a given source audio signal for the respectiveones of the selected subset of the frequency bands (filter banks) todetermine whether a given media source 120A-D provided the mediapresented by the media device 115.

A block diagram illustrated an example implementation of the mediasource comparator 235 of FIG. 2 is illustrated in FIG. 9. Turning toFIG. 9, the example media source comparator 235 includes an examplecross-correlator 905 to compare the subset of frequency bands selectedfor a given reference (e.g., media device) audio signal and source audiosignal pair. More specifically, in the illustrated example, thecross-correlator 905 use cross-correlation to process the frequency bandvalues of the reference (e.g., media device) audio signal and respectivefrequency band values of the given source audio signal for each one ofthe selected subset of the frequency bands (filter banks) to determinecorrelation results for each one of the selected subset of the frequencybands (filter banks). In general, stated mathematically, for the i^(th)frequency band (filter bank) in the subset of frequency bands (filterbanks) selected by the frequency band selector 230 for a given reference(e.g., media device) audio signal and source audio signal pair, theexample cross-correlator 905 determines a correlation result (c_(i)(n))by cross-correlating the frequency band values (PSD_REF_(i,m)) of thereference (e.g., media device) audio signal with the frequency bandvalues (PSD_SRC_(i,m)) of the given source audio signal according toEquation 6, over all possible delays, n, which is:

$\begin{matrix}{{c_{i}(n)} = {\sum\limits_{m}{\frac{\begin{matrix}( {{PSD\_ REF}_{i,m} - \overset{\_}{{PSD\_ REF}_{i}}} ) \\( {{PSD\_ SRC}_{i,{m + n}} - \overset{\_}{{PSD\_ SRC}_{i}}} )\end{matrix}}{( {\sigma_{{REF},i}{\cdot \sigma_{{SRC},i}}} )}.}}} & {{Equation}\mspace{14mu} 6}\end{matrix}$

In Equation 6, the cross-correlation of the frequency band values isperformed over a window of time delays (n) over a range, such as from −1sec. to +5 sec., or some other range. In Equation 6, PSD_REF_(i) is theaverage (or mean) of the frequency band values (PSD_REF_(i,m)) of thereference (e.g., media device) audio signal for the i^(th) frequencyband (filter bank), PSD_SRC_(i) is the average (or mean) of thefrequency band values (PSD_SRC_(i,m)) of the given source audio signalfor the i^(th) frequency band (filter bank), (σ_(REF,i)) is the standarddeviation of the frequency band values (PSD_REF_(i,m)) of the reference(e.g., media device) audio signal for the i^(th) frequency band (filterbank), and (σ_(SRC,i)) is the standard deviation of the frequency bandvalues (PSD_SRC_(i,m)) of the given source audio signal for the i^(th)frequency band (filter bank). The cross-correlation results (c_(i)(n))determined by the cross-correlator 905 for each one of the subset offrequency bands (filter banks) have values in the range of 0≦c_(i)(n)≦1.Also, the subset of frequency bands (filter banks) selected by thefrequency band selector 230 for comparison is empty (e.g., becauseEquation 5 is not satisfied for any frequency band), thencross-correlation result is set to a value of 0. Thus, thecross-correlation results c_(i)(n) can be interpreted as representinghow close, in terms of a percentage, the reference (e.g., media device)and source audio signals match in each one of the subset of frequencybands (filter banks).

In some examples, in each selected frequency band, the cross-correlator905 performs cross-correlation of the frequency band values for a givenreference (e.g., media device) audio signal and source audio signal pairover some or all of the possible shifts (e.g., delays) between thefrequency band values of the reference audio signal relative to thesource audio signal, or vice versa. In some examples, the frequency bandselector 230 may select a different subset of frequency bands (filterbanks) for each of the different shifts (delays) evaluated by thecross-correlator 905.

The example media source comparator 235 also includes an example matcher910 to combine the correlation results (c_(i)(n)) determined by thecross-correlator 905 for the subset of frequency bands (filter banks)selected for a given reference (e.g., media device) audio signal andsource audio signal pair to determine an overall match result for thegiven reference and source signal pair. In some examples, the matcher910 averages the correlation results (c_(i)(n)) for the subset offrequency bands (filter banks) to determine the overall match result forthe given reference and source signal pair. Stated mathematically, insuch examples, the matcher 910 determines the overall match for thegiven reference and source signal pair using Equation 7, which is:

$\begin{matrix}{{c(n)} = {\frac{1}{N_{Subset}}{\sum\limits_{i = 1}^{N_{Subset}}{{c_{i}(n)}.}}}} & {{Equation}\mspace{14mu} 7}\end{matrix}$

In Equation 7, N_(Subset) is the number of band (banks) included in thesubset of frequency bands (filter banks) selected for the givenreference (e.g., media device) audio signal and source audio signalpair. Also, the overall match (c(n)) for the given reference and sourcesignal pair determined using Equation 7 has a value in the range of0≦c(n)≦1.

In examples in which the overall match result is determined according toEquation 7, each one of the subset of frequency bands (filter banks)contributes equally to the overall match result. However, in suchexamples, frequency bands (filter banks) with low energy or flatfrequency responses contribute equally when compared with bands (banks)having high energy and/or that are dynamic. As such, in some examples,the media source comparator 235 further includes an example weighter 915to weight the correlation results (c_(i)(n)) determined for the subsetof frequency bands (filter banks) selected for a given reference (e.g.,media device) audio signal and source audio signal pair before thecorrelation results are combiner by the example matcher 910.

In some examples, the weighter 915 bases the weights determined forrespective bands (banks) in the subset of frequency bands (filter banks)on characteristics of the source signal being compared, and not on thereference (media device) signal being compared. Using the source signaland not the reference (media device) signal can be advantageous forseveral reasons. For example, if the source audio signal is obtained viaa cabled connection, whereas the reference (media device) audio signalis obtained via the microphone 135, then the source audio signal may besubstantially noise free, whereas the reference (media device) audiosignal may be corrupted by ambient noise and/or distorted by thefrequency response of the media device 115. In such examples, usingcharacteristics of the reference (media device) signal, instead of thesource audio signal, might result in weights that emphasize bands(banks) affected by the ambient noise and/or the frequency response ofthe media device 115, instead of emphasizing bands (banks) that can beused to identify the matching media source 120A-D.

In some examples, the weighter 915 determines the weights based solelyon the energy (e.g., PSD energy) in the different bands (banks) of thesubset of frequency bands (filter banks) selected for the givenreference and source signal pair. However, using just the energy mightfavor monotone audio signals with relatively high energy (e.g., becausea monotone audio signal is represented in the frequency domain as aconstant value over time and, thus, its energy would be constant andconstructively add over time). As such, in some examples, the weighter915 determines the weights for different bands (banks) of the subset offrequency bands (filter banks) selected for the given reference andsource signal pair as a combination of the energy of the band (bank) anda coefficient of variation determined for the band (bank). For example,the weighter 915 can determine the coefficient of variation (CV_(i)) forthe i^(th) frequency band (filter bank) according to Equation 8, whichis:

$\begin{matrix}{{CV}_{i} = {\frac{\sigma_{{SRC},i}}{{\overset{\_}{{PSD\_ SRC}_{i}}}^{2}}.}} & {{Equation}\mspace{14mu} 8}\end{matrix}$

In Equation 8, σ_(SRC,i) is the standard deviation of the frequency bandvalues (PSD_SRC_(i,m)) of the given source audio signal for the i^(th)frequency band (filter bank), and PSD_SRC_(i) ² is the square of theaverage (or mean) value of the frequency band values (PSD_SRC_(i,m)) ofthe given source audio signal for the i^(th) frequency band (filterbank). In such examples, the weighter 915 further determines the weight(w_(i)) for the i^(th) frequency band (filter bank) according toEquation 9, which is:

w _(i)=log₁₀(PSD_SRC_(i) ·CV_(i)).  Equation 9

In some examples in which the media source comparator 235 includes theexample weighter 915, the matcher 910 computes a weighted average of thecorrelation results (c_(i)(n)) for the subset of frequency bands (filterbanks) to determine the overall match result for the given reference andsource signal pair. Stated mathematically, in such examples, the matcher910 determines the overall match for the given reference and sourcesignal pair using Equation 10, which is:

$\begin{matrix}{{c(n)} = {\frac{1}{N_{Subset}}{\sum\limits_{i = 1}^{N_{Subset}}{\frac{w_{i}{c_{i}(n)}}{\sum\limits_{i = 1}^{N_{Subset}}w_{i}}.}}}} & {{Equation}\mspace{14mu} 10}\end{matrix}$

In Equation 10, N_(Subset) is the number of band (banks) included in thesubset of frequency bands (filter banks) selected for the givenreference (e.g., media device) audio signal and source audio signalpair. Also, the overall match (c(n)) for the given reference and sourcesignal pair determined using Equation 10 has a value in the range of0≦c(n)≦1.

In some examples, the matcher 910 of FIG. 9 performs an iterativematching process to determine the overall match (c(n)) for the givenreference and source signal pair. In some such examples, in a firstiteration, the matcher 910 determines the overall match (c(n)) for thegiven reference and source signal pair using, for example, Equation 7 orEquation 10. Then, the overall match (c(n)) is compared against thecorrelation results (c_(i)(n)) determined for respective ones of thesubset of frequency bands (filter banks), and the band (bank) with thelargest deviation (e.g., difference) from the overall match (c(n)) isexcluded from further comparison. During the next iteration, the matcher910 determines the overall match (c(n)) for the given reference andsource signal pair using, for example, Equation 7 or Equation 10, butexcluding the band (bank) identified in the preceding iteration. Thisiterative process continues for a number of iterations (e.g., 3 or someother value) until a remaining number (e.g., 5 or some other number) ofthe subset of frequency bands (filter banks) are included in thecomputation of the overall match (c(n)). The final, overall match (c(n))is then determined by the matcher 910 using this remaining number offrequency bands (filter banks).

In the illustrated example of FIG. 9, the example matcher 910 of theexample media source comparator 235 determines an overall match result(c(n)) for each possible reference (media device) and source audiosignal pair. For each possible reference (media device) and source audiosignal pair, the matcher 910 further determines whether the peak overallmatch result (c(n)) for a given reference (media device) and sourceaudio signal pair satisfies (e.g., exceeds) a match detection threshold(e.g., 0.8 or 80%, or some other value) and, if so, the delay (timeoffset, n) corresponding to the peak overall match result. If the peakoverall match result (c(n)) for a given reference (media device) andsource audio signal pair crosses the threshold, the media sourcecomparator 235 determines that the given media source is (or is likelyto be) the source of the media being presented by the media device 115for the current match detection time.

FIG. 10 illustrates and example overall match result 1000 output by theexample matcher 910 of the example media source comparator 235 for agiven reference (e.g., media device) and source audio signal pair usinga subset of frequency bands selected by the example frequency bandselector 230. In the illustrated example of FIG. 10, the overall matchresult 1000 is determined by the media source comparator 235 with shiftsof 32 ms. over a range of −5 sec. to 1 sec., and has a peak value at adelay of +96 ms (e.g., corresponding to c(n) for n=−3). Furthermore, thepeak value satisfies an example match detection threshold 1005.Accordingly, in the illustrated example of FIG. 10, the media sourcecomparator 235 determines that the given media source 120A-D yieldingthe overall match result 1000 is (or is likely to be) the source of themedia being presented by the media device 115 for the current matchdetection time.

In some operating scenarios, the overall match results (c(n)) formultiple possible reference (media device) and source audio signal pairsmay satisfy (e.g., exceed) the match detection threshold at a currentmatch detection time. Assuming that only one media source 120A-D isproviding the media being presented by the media device 115 at a giventime, one or more of these overall match results will correspond to afalse match detection. Thus, in some examples, the media sourcecomparator 235 of FIG. 9 further includes an example verifier 920 toverify the overall match results (c(n)) to attempt to reduce thepossibility of false match detections. In some examples, the verifier920 examines the delay (e.g., n) of successive overall match results(c(n)) for a given reference (media device) and source audio signal pairover a time period to verify the overall match results for the signalpair do not correspond to a false positive. The delays between thereference (media device) audio signal and the source audio signals fromdifferent media sources 120A-D may be different due to the differentaudio processing and/or propagation paths between the different mediasources 120A-D and the media device 115. However, although the delaysfor the different media sources 120A-D may be different, the delay for agiven media source 120A-D is generally fixed (or constant) over time,with minor fluctuations due to processing variations in the particularsource 120A-D and/or the media device 115. Thus, the verifier 920 of theillustrated example observes the delay associated with successiveoverall match results (c(n)) for a given reference (media device) andsource audio signal pair to determine whether the delay is stable, whichis indicative of a true match detection, or varying (e.g., jittering),which is indicative of a false match detection.

In some examples, for a given reference (media device) and source audiosignal pair, the example verifier 920 determines a standard deviation ofthe successive overall match results (c(n)) that satisfied (e.g.,exceeded) the match detection threshold over a time period and discardsthe overall match results as a false positive match if the standarddeviation is too great (e.g., exceeds a threshold delay, such as 5 timeunits (e.g., 5 units of 32 ms., which is 160 ms.), or some other value).Otherwise, if the standard deviation of the successive overall matchresults (c(n)) that satisfied (e.g., exceeded) the match detectionthreshold over the time period are not too great (e.g., do not exceedthe threshold delay), then the example verifier 920 retains the overallmatch results as a true positive match.

FIG. 11 illustrates an example deviation in the time delay associatedwith true positive match results determined by the example meter 110. Inthe illustrated example of FIG. 11, successive overall match results1100 output by the matcher 910 of the example media source comparator235 for a given reference (e.g., media device) and source audio signalpair which correspond to true positive source detections are overlaid onone another. Because the successive overall match results 1100correspond to true positive match results, the peak overall matchresults (which satisfy an example detection threshold 1105) are tightlylocated within a threshold delay around an average time delay of +96 ms.(e.g., corresponding to c(n) for n=−3). Thus, in such an example, theverifier 920 of the example media source comparator 235 would determinethat the values of the successive overall match results 1100 thatsatisfy the detection threshold 1105 have delays within the delaythreshold and, as such, these match results correspond to a truepositive detection match.

Conversely, FIG. 12 illustrates an example deviation in the time delayassociated with false positive match results determined by the examplemeter 110. In the illustrated example of FIG. 12, successive overallmatch results 1200 output by the matcher 910 of the example media sourcecomparator 235 for a given reference (e.g., media device) and sourceaudio signal pair which correspond to false positive source detectionsare overlaid on one another. Because the successive overall matchresults 1200 correspond to false positive match results, the peakoverall match results (which satisfy an example detection threshold1205) are spread through the range of examined time delays. Thus, insuch an example, the verifier 920 of the example media source comparator235 would determine that the values of the successive overall matchresults 1200 that satisfy the detection threshold 1205 have delaysexceeding the delay threshold and, as such, these match resultscorrespond to false positive detection matches and are to be discarded.

While example manners of implementing the meter 110 of FIG. 1 areillustrated in FIGS. 2-12, one or more of the elements, processes and/ordevices illustrated in FIGS. 2-12 may be combined, divided, re-arranged,omitted, eliminated and/or implemented in any other way. Further, theexample audio samplers 205A-D, the example audio sampler 210, theexample frequency transformers 215A-D, the example frequency transformer220, the example trending coefficient determiner 225, the examplefrequency band selector 230, the example media source comparator 235,the example filter bank aggregator 305, the example PSD determiner 310,the example PSD ratio evaluator 315, the example trending coefficientdirection comparator 805, the example trending coefficient valuecomparator 810, the example cross-correlator 905, the example matcher910, the example weighter 915, the example verifier 920 and/or, moregenerally, the example meter 110 of FIGS. 1-12 may be implemented byhardware, software, firmware and/or any combination of hardware,software and/or firmware. Thus, for example, any of the example audiosamplers 205A-D, the example audio sampler 210, the example frequencytransformers 215A-D, the example frequency transformer 220, the exampletrending coefficient determiner 225, the example frequency band selector230, the example media source comparator 235, the example filter bankaggregator 305, the example PSD determiner 310, the example PSD ratioevaluator 315, the example trending coefficient direction comparator805, the example trending coefficient value comparator 810, the examplecross-correlator 905, the example matcher 910, the example weighter 915,the example verifier 920 and/or, more generally, the example meter 110could be implemented by one or more analog or digital circuit(s), logiccircuits, programmable processor(s), application specific integratedcircuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)). When reading any of theapparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example meter 110,the example audio samplers 205A-D, the example audio sampler 210, theexample frequency transformers 215A-D, the example frequency transformer220, the example trending coefficient determiner 225, the examplefrequency band selector 230, the example media source comparator 235,the example filter bank aggregator 305, the example PSD determiner 310,the example PSD ratio evaluator 315, the example trending coefficientdirection comparator 805, the example trending coefficient valuecomparator 810, the example cross-correlator 905, the example matcher910, the example weighter 915 and/or the example verifier 920 is/arehereby expressly defined to include a tangible computer readable storagedevice or storage disk such as a memory, a digital versatile disk (DVD),a compact disk (CD), a Blu-ray disk, etc. storing the software and/orfirmware. Further still, the example meter 110 may include one or moreelements, processes and/or devices in addition to, or instead of, thoseillustrated in FIG. 1-12, and/or may include more than one of any or allof the illustrated elements, processes and devices.

Flowcharts representative of example machine readable instructions forimplementing the example meter 110, the example audio samplers 205A-D,the example audio sampler 210, the example frequency transformers215A-D, the example frequency transformer 220, the example trendingcoefficient determiner 225, the example frequency band selector 230, theexample media source comparator 235, the example filter bank aggregator305, the example PSD determiner 310, the example PSD ratio evaluator315, the example trending coefficient direction comparator 805, theexample trending coefficient value comparator 810, the examplecross-correlator 905, the example matcher 910, the example weighter 915and/or the example verifier 920 are shown in FIGS. 13A-B and 14-16. Inthese examples, the machine readable instructions comprise one or moreprograms for execution by a processor, such as the processor 1712 shownin the example processor platform 1700 discussed below in connectionwith FIG. 17. The one or more programs, or portion(s) thereof, may beembodied in software stored on a tangible computer readable storagemedium such as a CD-ROM, a floppy disk, a hard drive, a digitalversatile disk (DVD), a Blu-ray Disk™, or a memory associated with theprocessor 1712, but the entire program or programs and/or portionsthereof could alternatively be executed by a device other than theprocessor 1712 and/or embodied in firmware or dedicated hardware (e.g.,implemented by an ASIC, a PLD, an FPLD, discrete logic, etc.). Further,although the example program(s) is(are) described with reference to theflowcharts illustrated in FIGS. 13A-B and 14-16, many other methods ofimplementing the example meter 110, the example audio samplers 205A-D,the example audio sampler 210, the example frequency transformers215A-D, the example frequency transformer 220, the example trendingcoefficient determiner 225, the example frequency band selector 230, theexample media source comparator 235, the example filter bank aggregator305, the example PSD determiner 310, the example PSD ratio evaluator315, the example trending coefficient direction comparator 805, theexample trending coefficient value comparator 810, the examplecross-correlator 905, the example matcher 910, the example weighter 915and/or the example verifier 920 may alternatively be used. For example,with reference to the flowcharts illustrated in FIGS. 13A-B and 14-16,the order of execution of the blocks may be changed, and/or some of theblocks described may be changed, eliminated, combined and/or subdividedinto multiple blocks.

As mentioned above, the example processes of FIGS. 13A-B and 14-16 maybe implemented using coded instructions (e.g., computer and/or machinereadable instructions) stored on a tangible computer readable storagemedium such as a hard disk drive, a flash memory, a read-only memory(ROM), a compact disk (CD), a digital versatile disk (DVD), a cache, arandom-access memory (RAM) and/or any other storage device or storagedisk in which information is stored for any duration (e.g., for extendedtime periods, permanently, for brief instances, for temporarilybuffering, and/or for caching of the information). As used herein, theterm tangible computer readable storage medium is expressly defined toinclude any type of computer readable storage device and/or storage diskand to exclude propagating signals and to exclude transmission media. Asused herein, “tangible computer readable storage medium” and “tangiblemachine readable storage medium” are used interchangeably. Additionallyor alternatively, the example processes of FIGS. 13A-B and 14-16 may beimplemented using coded instructions (e.g., computer and/or machinereadable instructions) stored on a non-transitory computer and/ormachine readable medium such as a hard disk drive, a flash memory, aROM, a CD, a DVD, a cache, a RAM and/or any other storage device orstorage disk in which information is stored for any duration (e.g., forextended time periods, permanently, for brief instances, for temporarilybuffering, and/or for caching of the information). As used herein, theterm non-transitory computer readable medium is expressly defined toinclude any type of computer readable storage device and/or storage diskand to exclude propagating signals and to exclude transmission media. Asused herein, when the phrase “at least” is used as the transition termin a preamble of a claim, it is open-ended in the same manner as theterm “comprising” is open ended. Also, as used herein, the terms“computer readable” and “machine readable” are considered equivalentunless indicated otherwise.

An example program 1300 that may be executed to implement the examplemeter 110 is represented by the flowchart shown in FIGS. 13A-B. Theexample program 1300 may be executed at predetermined intervals, basedon an occurrence of a predetermined event, etc., or any combinationthereof. With reference to the preceding figures and associated writtendescriptions, the example program 1300 of FIGS. 13A-B begins executionat blocks 1305 and 1310 of FIG. 13A at which the meter 110 executesparallel processing threads to process a reference (e.g., media device)audio signal obtained from the media device 115 at the reference input125 of the meter 110, and to process source audio signals obtained fromthe media sources 120A-D at the source inputs 130A-D of the meter 110.For example, at block 1305, the audio sampler 210 of the meter 110samples the reference (e.g., media device) audio signal obtained at thereference input 125 to obtain a reference audio block, as describedabove. At block 1315, the frequency transformer 220 of the meter 110transforms the sampled reference (e.g., media device) audio blockobtained at block 1305 into a frequency representation (or frequencytransform) of the reference (e.g., media device) audio signal, asdescribed above. At block 1320, the trending coefficient determiner 225of the meter 110 processes the frequency representation (e.g., frequencytransform) obtained at block 1315 to determine trending coefficients forthe reference (e.g., media device) audio signal over a set of frequencybands (e.g., filter banks), as described above. Example machine readableinstructions that may be used to perform the processing at block 1320are illustrated in FIG. 14, which is described in further detail below.

At block 1310, the meter 110 begins processing source signals obtainedfrom respective ones of the media sources 120A-D. For example, at block1325, the audio samplers 205A-D of the meter 110 sample the source audiosignal obtained at the source input 130A-D for the next media source120A-D to be processed to obtain a source audio block for that mediasource 120A-D, as described above. At block 1330, the frequencytransformers 215A-D of the meter 110 transform the sampled source audioblock obtained at block 1330 into a frequency representation (orfrequency transform) of the source audio signal, as described above. Atblock 1335, the trending coefficient determiner 225 of the meter 110processes the frequency representation (e.g., frequency transform)obtained at block 1330 to determine trending coefficients for the givensource audio signal over the set of frequency bands (e.g., filterbanks), as described above. Example machine readable instructions thatmay be used to perform the processing at block 1335 are illustrated inFIG. 14, which is described in further detail below. At block 1340, themeter 110 causes the foregoing processing to repeat until trendingcoefficients are determined for all of the media sources 120A-D for thecurrent detection time.

Processing continues at block 1345 of FIG. 13B, at which the meter 110performs pairwise comparison between the reference audio signal obtainedfrom the media device 115 and respective ones of the audio signalsobtained from the media sources 120A-D. For example, at block 1350, thefrequency band selector 230 updates the selected subset of frequencybands (filter banks) to be used to perform the pairwise comparison of agiven reference (e.g., media device) audio signal and source audiosignal pair, as described above. Example machine readable instructionsthat may be used to perform the processing at block 1350 are illustratedin FIG. 15, which is described in further detail below. At block 1355,the media source comparator 235 evaluates the frequency band values ofthe reference (e.g., media device) audio signal and source audio signalpair obtained at blocks 1315 and 1330 for the subset of frequency bands(filter banks) selected at block 1350 to determine an overall matchresult indicating whether the source audio from the given media source120A-D matches the reference audio from the media device 115. Examplemachine readable instructions that may be used to perform the processingat block 1355 are illustrated in FIG. 16, which is described in furtherdetail below. At block 1360, the meter 110 repeats the foregoingprocessing until overall match results are obtained for each possiblereference (e.g., media device) audio signal and source audio signalpair.

At block 1365, the media source comparator 235 compares the overallmatch results for the different possible reference (e.g., media device)audio signal and source audio signal pairs (and performs validation, asdescribed above) to identify the source audio signal that matches (or isthe most likely match to) the reference (e.g., media device) audiosignal. For example, if one valid overall match result corresponding toone possible reference (e.g., media device) audio signal and sourceaudio signal pair is determined by the media source comparator 235, thenthe source audio signal of that pair is determined to match thereference (e.g., media device) audio signal. However, if multiple validoverall match results corresponding to multiple possible reference(e.g., media device) audio signal and source audio signal pairs aredetermined by the media source comparator 235, then the media sourcecomparator 235 may select the particular source audio signal paircorresponding to the largest overall match result to be the matchingsource signal for the current match detection time period. Next, atblock 1370, the meter 1370 determines whether monitoring is to continuefor a next match detection time. If monitoring is to continue (block1370), then processing returns to block 1305 and 1310 at which the meter110 obtains and processes the next reference (e.g., media device) andsource audio blocks for the next match detection time period.

An example program 1400 that may be executed to implement the exampletrending coefficient determiner 225 of the example meter 110, and/or toperform the processing at blocks 1320 and/or 1335 of FIG. 13A, isrepresented by the flowchart shown in FIG. 14. With reference to thepreceding figures and associated written descriptions, the exampleprogram 1400 of FIG. 14 begins execution at block 1405 at which thefilter bank aggregator 305 of the trending coefficient determiner 225determines the boundaries for the set of frequency bands (filter banks)to be examined, and aggregates the FFT bins of the frequency transformof the given audio signal (e.g., reference or source audio signal) beingprocessed into the aggregated frequency bands (filter banks), asdescribed above. At block 1410, the PSD determiner 310 of the trendingcoefficient determiner 225 determines, as described above, the frequencyband values (e.g., PSD values) of the given audio signal for each band(bank) of the set of frequency bands (filter banks) obtained at block1405.

At block 1415, the trending coefficient determiner 225 beginsdetermining the trending coefficients for the given audio signal for therespective bands (banks) of the set of frequency bands (filter banks).For example, at block 1420, the PSD ratio evaluator 315 determines thetrending coefficient for a given frequency band (filter bank) to be aratio of the current and prior frequency band values (e.g., PSD values)for the given frequency band (filter bank), as described above. As alsodescribed above, the frequency band values (e.g., PSD values) processedat block 1420 can be running averages of the frequency band values(e.g., PSD values) for the given frequency band (filter bank). At block1425, the trending coefficient determiner 225 causes the foregoingprocessing to repeat until a trending coefficient for the given audiosignal has been determined for each one of the bands (banks) in the setof frequency bands (filter banks).

An example program 1350P that may be executed to implement the examplefrequency band selector 230 of the example meter 110, and/or to performthe processing at block 1350 of FIG. 13B, is represented by theflowchart shown in FIG. 15. With reference to the preceding figures andassociated written descriptions, the example program 1350P of FIG. 15begins execution at block 1505 at which the trending coefficientdirection comparator 805 of the frequency band selector 230 identifies afirst subset of frequency bands (filter banks) for which the reference(e.g., media device) audio signal and a given one of the source audiosignals have trending coefficients with matching directions, asdescribed above. At block 1510, the frequency band selector 230determines whether the first subset of frequency bands (filter banks)identified at block 1510 includes more than a limiting number (e.g., 8or some other number) of bands (banks), as described above. If the firstsubset of frequency bands (filter banks) does not include more than thelimiting number of bands (banks), then match comparison will beperformed based on the first subset of frequency bands (filter banks)selected at block 1510. However, if the first subset of frequency bands(filter banks) does include more than the limiting number of bands(banks), then at block 1515, the trending coefficient value comparator810 of the frequency band selector 230 identifies a limiting number(e.g., 8 or some other number) of the first subset of frequency bands(filter banks), which have trending coefficients with matchingdirections for the reference (e.g., media device) audio signal and thegiven source audio signal, that also have the closest matching values oftheir respective trending coefficients. At block 1520, the trendingcoefficient value comparator 810 determines a second subset of frequencybands (filter banks), which includes the limiting number of bands(banks) identified at block 1515. This second subset of frequency bands(filter banks) is then used to perform match comparison.

An example program 1355P that may be executed to implement the examplemedia source comparator 235 of the example meter 110, and/or to performthe processing at block 1355 of FIG. 13B, is represented by theflowchart shown in FIG. 16. With reference to the preceding figures andassociated written descriptions, the example program 1355P of FIG. 16begins execution at block 1605 at which the media source comparator 235begins processing of the subset of frequency bands (filter banks)selected by the frequency band selector 230 for a given reference (e.g.,media device) audio signal and source audio signal pair to perform apairwise comparison of the reference and source signal to determinewhether the source signal matches the reference (e.g., media device)signal, as described above. For example, at block 1610, thecross-correlator 905 cross-correlates the frequency band values of thereference (e.g., media device) audio signal and respective frequencyband values of the given source audio signal for each one of theselected subset of frequency bands (filter banks) to determinecorrelation results for each one of the selected subset of the frequencybands (filter banks). At block 1615, the cross-correlator 905 continuesprocessing until correlation results are determined for all of theselected subset of frequency bands (banks).

At block 1620, the weighter 915 of the media source comparator 235weights the correlation results determined at block 1615, and thematcher 910 of the media source comparator 235 combines the weightedcorrelation results for the selected subset of frequency bands (banks),as described above. At block 1625, the matcher 910 identifies thecorrelation result(s) satisfying a matching threshold, as describedabove. At block 1630, the matcher 910 stores the matching correlationresult, which satisfying the matching threshold, over time. At block1635, the verifier 920 of the media source comparator 235 uses thestandard deviations of time delays associated with the stored matchingcorrelation results to eliminate false detections, as described above.

FIG. 17 is a block diagram of an example processor platform 1700 capableof executing the instructions of FIGS. 13A-B and 14-16 to implement theexample meter 110, the example audio samplers 205A-D, the example audiosampler 210, the example frequency transformers 215A-D, the examplefrequency transformer 220, the example trending coefficient determiner225, the example frequency band selector 230, the example media sourcecomparator 235, the example filter bank aggregator 305, the example PSDdeterminer 310, the example PSD ratio evaluator 315, the exampletrending coefficient direction comparator 805, the example trendingcoefficient value comparator 810, the example cross-correlator 905, theexample matcher 910, the example weighter 915 and/or the exampleverifier 920 of FIGS. 1-12. The processor platform 1700 can be, forexample, an embedded processor system, a server, a personal computer, amobile device (e.g., a cell phone, a smart phone, a tablet such as aniPad™), a personal digital assistant (PDA), an Internet appliance, a DVDplayer, a CD player, a digital video recorder, a Blu-ray player, agaming console, a personal video recorder, a set top box a digitalcamera, or any other type of computing device.

The processor platform 1700 of the illustrated example includes aprocessor 1712. The processor 1712 of the illustrated example ishardware. For example, the processor 1712 can be implemented by one ormore integrated circuits, logic circuits, microprocessors or controllersfrom any desired family or manufacturer.

The processor 1712 of the illustrated example includes a local memory1713 (e.g., a cache). The processor 1712 of the illustrated example isin communication with a main memory including a volatile memory 1714 anda non-volatile memory 1716 via a link 1718. The link 1718 may beimplemented by a bus, one or more point-to-point connections, etc., or acombination thereof. The volatile memory 1714 may be implemented bySynchronous Dynamic Random Access Memory (SDRAM), Dynamic Random AccessMemory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM) and/or anyother type of random access memory device. The non-volatile memory 1716may be implemented by flash memory and/or any other desired type ofmemory device. Access to the main memory 1714, 1716 is controlled by amemory controller.

The processor platform 1700 of the illustrated example also includes aninterface circuit 1720. The interface circuit 1720 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), and/or a PCI express interface.

In the illustrated example, one or more input devices 1722 are connectedto the interface circuit 1720. The input device(s) 1722 permit(s) a userto enter data and commands into the processor 1712. The input device(s)can be implemented by, for example, an audio sensor, a microphone, acamera (still or video), a keyboard, a button, a mouse, a touchscreen, atrack-pad, a trackball, a trackbar (such as an isopoint), a voicerecognition system and/or any other human-machine interface. Also, manysystems, such as the processor platform 1700, can allow the user tocontrol the computer system and provide data to the computer usingphysical gestures, such as, but not limited to, hand or body movements,facial expressions, and face recognition.

One or more output devices 1724 are also connected to the interfacecircuit 1720 of the illustrated example. The output devices 1724 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay, a cathode ray tube display (CRT), a touchscreen, a tactileoutput device, a printer and/or speakers). The interface circuit 1720 ofthe illustrated example, thus, typically includes a graphics drivercard, a graphics driver chip or a graphics driver processor.

The interface circuit 1720 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem and/or network interface card to facilitate exchange of data withexternal machines (e.g., computing devices of any kind) via a network1726 (e.g., an Ethernet connection, a digital subscriber line (DSL), atelephone line, coaxial cable, a cellular telephone system, etc.).

The processor platform 1700 of the illustrated example also includes oneor more mass storage devices 1728 for storing software and/or data.Examples of such mass storage devices 1728 include floppy disk drives,hard drive disks, solid state drive (flash memory), compact disk drives,Blu-ray disk drives, RAID (redundant array of independent disks)systems, and digital versatile disk (DVD) drives.

Coded instructions 1732 corresponding to the instructions of FIGS. 13A-Band 14-16 may be stored in the mass storage device 1728, in the volatilememory 1714, in the non-volatile memory 1716, in the local memory 1713and/or on a removable tangible computer readable storage medium, such asa CD or DVD 1736.

Although certain example methods, apparatus and articles of manufacturehave been disclosed herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

What is claimed is:
 1. A meter comprising: a comparator to: comparefrequency band values of a first audio signal with correspondingfrequency band values of a second audio signal for a first subset of aset of frequency bands to determine a first comparison result; comparethe frequency band values of the first audio signal with correspondingfrequency band values of a third audio signal for a different secondsubset of the set of frequency bands to determine a second comparisonresult; and determine a source of the first audio signal based on thefirst comparison result and the second comparison result; and a selectorto select the first and second subsets of the set of frequency bands. 2.The meter of claim 1, further including: a first audio input to receivethe first audio signal from a monitored media device; a second audioinput to receive the second audio signal from a first one of a pluralityof media sources providing media to the media device; and a third audioinput to receive the third audio signal from a second one of theplurality of media sources.
 3. The meter of claim 2, wherein thefrequency band values of the first audio signal, the frequency bandvalues of the second audio signal and the frequency band values of thethird audio signal are respective power spectral density values, andfurther including a frequency transformer to: process samples of thefirst audio signal to determine power spectral density values of thefirst audio signal for the set of frequency bands; process samples ofthe second audio signal to determine power spectral density values ofthe second audio signal for the set of frequency bands; and processsamples of the third audio signal to determine power spectral densityvalues of the third audio signal for the set of frequency bands.
 4. Themeter of claim 1, wherein the selector is to select the first subset ofthe set of frequency bands based on a first set of trending coefficientsdetermined for the first audio signal for the set of frequency bands anda second set of trending coefficients determined for the second audiosignal for the set of frequency bands, and the selector is to select thesecond subset of the set of frequency bands based on the first set oftrending coefficients determined for the first audio signal for the setof frequency bands and a third set of trending coefficients determinedfor the third audio signal for the set of frequency bands.
 5. The meterof claim 4, further including a coefficient determiner to determine thefirst set of trending coefficients, the second set of trendingcoefficients and the third set of trending coefficients, the coefficientdeterminer to determine the first set of trending coefficients by:accessing a first set of frequency band values determined for the set offrequency bands from a first block of audio samples of the first audiosignal; accessing a second set of frequency band values determined forthe set of frequency bands from a subsequent second block of audiosamples of the first audio signal; and determining the first set oftrending coefficients based on ratios of respective ones of the secondset of frequency band values to respective ones of the first set offrequency band values.
 6. The meter of claim 5, wherein the selector isto select the first subset of the set of frequency bands to correspondto ones of the set of frequency bands for which the first set oftrending coefficients determined for the first audio signal and thesecond set of trending coefficients determined for the second audiosignal have matching directions, and the selector is to select thesecond subset of the set of frequency bands to correspond to ones of theset of frequency bands for which the first set of trending coefficientsdetermined for the first audio signal and the third set of trendingcoefficients determined for the second audio signal have matchingdirections.
 7. The meter of claim 6, wherein a first one of the firstset of trending coefficients determined for the first audio signal and acorresponding first one of the second set of trending coefficientsdetermined for the second audio signal have matching directions wheneither (1) both the first one of the first set of trending coefficientsand the corresponding first one of the second set of trendingcoefficients exceed a threshold or (2) both the first one of the firstset of trending coefficients and the corresponding first one of thesecond set of trending coefficients do not exceed the threshold.
 8. Ametering method comprising: comparing, by executing an instruction witha processor, frequency band values of a first audio signal withcorresponding frequency band values of a second audio signal for a firstsubset of a set of frequency bands to determine a first comparisonresult; comparing, by executing an instruction with the processor, thefrequency band values of the first audio signal with correspondingfrequency band values of a third audio signal for a different secondsubset of the set of frequency bands to determine a second comparisonresult; and determining, by executing an instruction with the processor,a source of the first audio signal based on the first comparison resultand the second comparison result.
 9. The method of claim 8, wherein thefrequency band values of the first audio signal, the frequency bandvalues of the second audio signal and the frequency band values of thethird audio signal are respective power spectral density values, andfurther including: processing samples of the first audio signal todetermine power spectral density values of the first audio signal forthe set of frequency bands; processing samples of the second audiosignal to determine power spectral density values of the second audiosignal for the set of frequency bands; and processing samples of thethird audio signal to determine power spectral density values of thethird audio signal for the set of frequency bands.
 10. The method ofclaim 8, wherein the selecting of the first subset of the set offrequency bands is based on a first set of trending coefficientsdetermined for the first audio signal for the set of frequency bands anda second set of trending coefficients determined for the second audiosignal for the set of frequency bands, and the selecting of the secondsubset of the set of frequency bands is based on the first set oftrending coefficients determined for the first audio signal for the setof frequency bands and a third set of trending coefficients determinedfor the third audio signal for the set of frequency bands.
 11. Themethod of claim 10, further including determining the first set oftrending coefficients by: accessing a first set of frequency band valuesdetermined for the set of frequency bands from a first block of audiosamples of the first audio signal; accessing a second set of frequencyband values determined for the set of frequency bands from a subsequentsecond block of audio samples of the first audio signal; and determiningthe first set of trending coefficients based on ratios of respectiveones of the second set of frequency band values to respective ones ofthe first set of frequency band values.
 12. The method of claim 11,wherein the selecting of the first subset of the set of frequency bandsincludes selecting the first subset of the set of frequency bands tocorrespond to ones of the set of frequency bands for which the first setof trending coefficients determined for the first audio signal and thesecond set of trending coefficients determined for the second audiosignal have matching directions, and the selecting of the second subsetof the set of frequency bands includes selecting the second subset ofthe set of frequency bands to correspond to ones of the set of frequencybands for which the first set of trending coefficients determined forthe first audio signal and the third set of trending coefficientsdetermined for the second audio signal have matching directions.
 13. Themethod of claim 12, wherein a first one of the first set of trendingcoefficients determined for the first audio signal and a correspondingfirst one of the second set of trending coefficients determined for thesecond audio signal have matching directions when either (1) both thefirst one of the first set of trending coefficients and thecorresponding first one of the second set of trending coefficientsexceed a threshold or (2) both the first one of the first set oftrending coefficients and the corresponding first one of the second setof trending coefficients do not exceed the threshold.
 14. The method ofclaim 8, further including reporting metering data including anidentification of the source of the first audio signal to a dataprocessing facility via a network.
 15. A non-transitory computerreadable medium comprising computer readable instructions that, whenexecuted, cause a processor to at least: compare frequency band valuesof a first audio signal with corresponding frequency band values of asecond audio signal for a first subset of a set of frequency bands todetermine a first comparison result; compare the frequency band valuesof the first audio signal with corresponding frequency band values of athird audio signal for a different second subset of the set of frequencybands to determine a second comparison result; and determine a source ofthe first audio signal based on the first comparison result and thesecond comparison result.
 16. The non-transitory computer readablemedium of claim 15, wherein the frequency band values of the first audiosignal, the frequency band values of the second audio signal and thefrequency band values of the third audio signal are respective powerspectral density values, and the instructions, when executed, furthercause the processor to: process samples of the first audio signal todetermine power spectral density values of the first audio signal forthe set of frequency bands; process samples of the second audio signalto determine power spectral density values of the second audio signalfor the set of frequency bands; and process samples of the third audiosignal to determine power spectral density values of the third audiosignal for the set of frequency bands.
 17. The non-transitory computerreadable medium of claim 15, wherein the instructions, when executed,cause the processor to select the first subset of the set of frequencybands based on a first set of trending coefficients determined for thefirst audio signal for the set of frequency bands and a second set oftrending coefficients determined for the second audio signal for the setof frequency bands, and to select the second subset of the set offrequency bands based on the first set of trending coefficientsdetermined for the first audio signal for the set of frequency bands anda third set of trending coefficients determined for the third audiosignal for the set of frequency bands.
 18. The non-transitory computerreadable medium of claim 17, wherein the instructions, when executed,further cause the processor to: access a first set of frequency bandvalues determined for the set of frequency bands from a first block ofaudio samples of the first audio signal; access a second set offrequency band values determined for the set of frequency bands from asubsequent second block of audio samples of the first audio signal; anddetermine the first set of trending coefficients based on ratios ofrespective ones of the second set of frequency band values to respectiveones of the first set of frequency band values.
 19. The non-transitorycomputer readable medium of claim 18, wherein instructions, whenexecuted, cause the processor to selecting the first subset of the setof frequency bands to correspond to ones of the set of frequency bandsfor which the first set of trending coefficients determined for thefirst audio signal and the second set of trending coefficientsdetermined for the second audio signal have matching directions, and toselect the second subset of the set of frequency bands to correspond toones of the set of frequency bands for which the first set of trendingcoefficients determined for the first audio signal and the third set oftrending coefficients determined for the second audio signal havematching directions.
 20. The non-transitory computer readable medium ofclaim 19, wherein a first one of the first set of trending coefficientsdetermined for the first audio signal and a corresponding first one ofthe second set of trending coefficients determined for the second audiosignal have matching directions when either (1) both the first one ofthe first set of trending coefficients and the corresponding first oneof the second set of trending coefficients exceed a threshold or (2)both the first one of the first set of trending coefficients and thecorresponding first one of the second set of trending coefficients donot exceed the threshold.